The present volume explores the broad impact of artificial intelligence in education by presenting a broad range of perspectives from some leading experts in the field. An initial chapter tackles macro level considerations from a social and anthropological perspective. Further, chapters explore more specific topics, ranging from philosophical aspects to the implications of AI in pedagogy and andragogy. The final chapter attempts to integrate the disparate aspects of the dialogue into a cohesive voice.

Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and ultimately accelerate the progress towards SDG 4. However, these rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. This publication offers guidance for policy-makers on how best to leverage the opportunities and address the risks, presented by the growing connection between AI and education. It starts with the essentials of AI: definitions, techniques and technologies. It continues with a detailed analysis of the emerging trends and implications of AI for teaching and learning, including how we can ensure the ethical, inclusive and equitable use of AI in education, how education can prepare humans to live and work with AI, and how AI can be applied to enhance education. It finally introduces the challenges of harnessing AI to achieve SDG 4 and offers concrete actionable recommendations for policy-makers to plan policies and programmes for local contexts. [Publisher summary, ed]

This book includes contributions by scholars from a variety of disciplines, the dialogue and discourse on how AI (artificial intelligence) development includes and/or excludes pedagogical educational learning theories focused on the learner. A call from Educational Leaders Without Borders (ELWB) was issued to scholars from across the globe who were asked to write a vignette described as an evocative description or account on how education leaders envision education in 2051 and A.I. beyond mere product purchase. These vignettes should engage us in questions as to how the development and use of AI technologies are shaped. As educators who believe education should be established on social justice beliefs and practices, our review of literature shows there are no books addressing the complexities of A.I. development and the role of educators. The futuristic element is unique in its approach to imagine a socially just better world in which to inspire educators. This unique feature encourages creativity in how one addresses the call to imagine a future world and our role as educators in that world.

Artificial Intelligence in Education conference 2009 (AIED) is part of a series of biennial international conferences for top quality research in intelligent systems and cognitive science for educational computing applications. This title covers papers presented at the Artificial Intelligence in Education conference 2009 (AIED).

The nature of technology has changed since Artificial Intelligence in Education (AIED) was conceptualized as a research community and Interactive Learning Environments were initially developed.

This publication covers papers presented at AIED2009, part of an ongoing series of biennial international conferences for top quality research in intelligent systems and cognitive science for educational computing applications. The conference provides opportunities for the cross-fertilization of techniques from many fields that make up this interdisciplinary research area, including: artificial intelligence, computer science, cognitive and learning sciences, education, educational technology, psychology, philosophy, sociology, anthropology, linguistics, and the many domain-specific areas for which AIED systems have been designed and evaluated. AIED2009 focuses on the theme "Building learning systems that care: from knowledge representation to affective modelling". The key research question is how to tackle the complex issues related to building learning systems that care, ranging from representing knowledge and context to modelling social, cognitive, metacognitive, and affective dimensions. This requires multidisciplinary research that links theory and technology from artificial intelligence, cognitive science, and computer science with theory and practice from education and the social sciences.